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1. 发明授权

US09369481B2 Incident triage engine 有权
标题翻译：事故分流引擎
公开(公告)号：US09369481B2
公开(公告)日：2016-06-14
申请号：US14247322
申请日：2014-04-08
申请人： Accenture Global Services Limited
发明人： Joshua Z. Howes , Walid Negm , James J. Solderitsch , Ashish Jotwani , Matthew Carver
IPC分类号： G06F11/00 , H04L29/06 , G06F21/57 , G06Q10/10 , G06F21/55
CPC分类号： H04L63/1433 , G06F21/554 , G06F21/577 , G06Q10/10 , H04L63/1416
摘要： An incident triage engine performs incident triage in a system by prioritizing responses to incidents within the system. One prioritization method may include receiving attributes of incidents and assets in the system, generating cumulative loss forecasts for the incidents, and prioritizing the responses to the incidents based on the cumulative loss forecasts for the incidents. Another prioritization method may include determining different arrangements of incidents within a response queue, calculating cumulative queue loss forecasts for the different arrangements of incidents within the response queue, and arranging the incidents in the response queue based on the arrangement of incidents that minimizes the total loss to the system over the resolution of all of the incidents present in the response queue.
摘要翻译：事件分类引擎通过对系统内事件的响应进行优先排序来对系统进行事件分类。一种优先化方法可以包括接收系统中的事件和资产的属性，生成事件的累积损失预测，并根据事件的累积损失预测对事件的响应进行优先级排序。另一个优先化方法可以包括确定响应队列内的事件的不同布置，计算响应队列内的事件的不同布置的累积队列丢失预测，以及基于最小化总损失的事件的布置将事件排列在响应队列中到系统解决所有响应队列中出现的事件。

2. 发明授权

US09531743B2 Data trend analysis 有权
公开(公告)号：US09531743B2
公开(公告)日：2016-12-27
申请号：US15147471
申请日：2016-05-05
申请人： Accenture Global Services Limited
发明人： Joshua Z. Howes , James Solderitsch , Ryan M. Lasalle , David W. Rozmiarek , Eric A. Ellett
IPC分类号： G06F11/00 , H04L29/06 , G06F17/30 , G06F21/55 , G06F17/27
CPC分类号： H04L63/1425 , G06F17/2785 , G06F17/30705 , G06F17/30716 , G06F17/30734 , G06F17/30864 , G06F21/55 , G06F21/552 , G06F2221/2151
摘要： According to an example, a method for data trend analysis may include retrieving data from data sources, associating the data with a time, and identifying co-occurrences of terms and concepts within the data. In response to determining that co-occurrences of term and concept pairs reach a predefined threshold, the method may include adding the term and concept pairs to an ontology. The method may include logging occurrences of terms in the ontology within the data with respect to associated data times, identifying a plurality of time periods, and for one of the plurality of time periods and for the logged terms, determining a first score indicative of a weighted term frequency metric for a logged term within the data during the one time period, and determining a second score indicative of a commonality of a presence of the logged term within the data among the plurality of time periods.

3. 发明授权

US09355172B2 Data trend analysis 有权
标题翻译：数据趋势分析
公开(公告)号：US09355172B2
公开(公告)日：2016-05-31
申请号：US13826965
申请日：2013-03-14
申请人： Accenture Global Services Limited
发明人： Joshua Z. Howes , James Solderitsch , Ryan M. LaSalle , David W. Rozmiarek , Eric A. Ellett
IPC分类号： G06F11/00 , G06F17/30 , G06F21/55
CPC分类号： H04L63/1425 , G06F17/2785 , G06F17/30705 , G06F17/30716 , G06F17/30734 , G06F17/30864 , G06F21/55 , G06F21/552 , G06F2221/2151
摘要： According to an example, a method for data trend analysis may include retrieving data from data sources, associating the data with a time, and identifying co-occurrences of terms and concepts within the data. In response to determining that co-occurrences of term and concept pairs reach a predefined threshold, the method may include adding the term and concept pairs to an ontology. The method may include logging occurrences of terms in the ontology within the data with respect to associated data times, identifying a plurality of time periods, and for one of the plurality of time periods and for the logged terms, determining a first score indicative of a weighted term frequency metric for a logged term within the data during the one time period, and determining a second score indicative of a commonality of a presence of the logged term within the data among the plurality of time periods.
摘要翻译：根据示例，用于数据趋势分析的方法可以包括从数据源检索数据，将数据与时间相关联，以及识别数据内的术语和概念的共同出现。响应于确定术语和概念对的共同出现达到预定阈值，该方法可以包括将术语和概念对添加到本体。该方法可以包括在数据中关于相关联的数据时间，识别多个时间段以及对于多个时间段中的一个以及对于记录的术语来记录本体内的术语中的术语的出现，确定表示一个在所述一个时间段期间在所述数据内记录的项目的加权项频率度量，以及确定指示所述多个时间段内的所述数据内记录项目的存在的共同性的第二分数。

4. 发明申请

US20140283048A1 DATA TREND ANALYSIS 有权
标题翻译：数据趋势分析
公开(公告)号：US20140283048A1
公开(公告)日：2014-09-18
申请号：US13826965
申请日：2013-03-14
申请人： ACCENTURE GLOBAL SERVICES LIMITED
发明人： Joshua Z. Howes , James Solderitsch , Ryan M. LaSalle , David W. Rozmiarek , Eric A. Ellett
IPC分类号： G06F17/30 , G06F21/55
CPC分类号： H04L63/1425 , G06F17/2785 , G06F17/30705 , G06F17/30716 , G06F17/30734 , G06F17/30864 , G06F21/55 , G06F21/552 , G06F2221/2151
摘要： According to an example, a method for data trend analysis may include retrieving data from data sources, associating the data with a time, and identifying co-occurrences of terms and concepts within the data. In response to determining that co-occurrences of term and concept pairs reach a predefined threshold, the method may include adding the term and concept pairs to an ontology. The method may include logging occurrences of terms in the ontology within the data with respect to associated data times, identifying a plurality of time periods, and for one of the plurality of time periods and for the logged terms, determining a first score indicative of a weighted term frequency metric for a logged term within the data during the one time period, and determining a second score indicative of a commonality of a presence of the logged term within the data among the plurality of time periods.
摘要翻译：根据示例，用于数据趋势分析的方法可以包括从数据源检索数据，将数据与时间相关联，以及识别数据内的术语和概念的共同出现。响应于确定术语和概念对的共同出现达到预定阈值，该方法可以包括将术语和概念对添加到本体。该方法可以包括在数据中关于相关联的数据时间，识别多个时间段以及对于多个时间段中的一个以及对于记录的术语来记录本体内的术语中的术语的出现，确定表示一个在所述一个时间段期间在所述数据内记录的项目的加权项频率度量，以及确定指示所述多个时间段内的所述数据内记录项目的存在的共同性的第二分数。

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